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Editorial: Trends in Neuroergonomics View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Frontiers - Publisher Connector EDITORIAL published: 05 April 2017 doi: 10.3389/fnhum.2017.00165 Editorial: Trends in Neuroergonomics Klaus Gramann 1, 2*, Stephen H. Fairclough 3, Thorsten O. Zander 1, 4 and Hasan Ayaz 5, 6, 7 1 Department of Psychology and Ergonomics, Berlin Institute of Technology (TU Berlin), Berlin, Germany, 2 Center for Advanced Neurological Engineering, University of California, San Diego, San Diego, CA, USA, 3 School of Natural Sciences and Psychology, Liverpool John Moores University, Liverpool, UK, 4 Team PhyPA, Berlin Institute of Technology (TU Berlin), Berlin, Germany, 5 School of Biomedical Engineering, Science and Health Systems, Drexel University, Philadelphia, PA, USA, 6 Department of Family and Community Health, University of Pennsylvania, Philadelphia, PA, USA, 7 Division of General Pediatrics, Children’s Hospital of Philadelphia, Philadelphia, PA, USA Keywords: neuroergonomics, human-machine interaction, brain-computer interface, mobile brain/body imaging, physiological computing, EEG/ERP, NIRS/fNIRS, tDCS Editorial on the Research Topic Trends in Neuroergonomics NEW METHODS IN NEUROERGONOMICS This Research Topic is dedicated to Professor Raja Parasuraman who unexpectedly passed on March 22nd 2015. Raja Parasuraman’s pioneering work led to the emergence of Neuroergonomics as a new scientific field. Neuroergonomics is defined as the study of the human brain in relation to performance at work and everyday settings (Parasuraman, 2003; Parasuraman and Rizzo, 2008). Since the advent of Neuroergonomics, significant progress has been made with respect to methodology and tools for the investigation of the brain and behavior at work. This is especially the case for neuroscientific methods where the availability of ambulatory hardware, wearable sensors, and advanced data analyses allow for imaging of brain dynamics in humans in applied environments. For neuroergonomics, the application of brain imaging in real-world scenarios is highly desirable as an investigation tool. Traditionally, brain imaging experiments in human factors research tend to avoid active behavior for fear of artifacts contaminating the signal of interest. Here, the development of new data analyses techniques as well as the combination of different methods providing complementary insights into brain and behavioral dynamics allow for new insights into Edited and reviewed by: the human-machine interaction. To overcome the problem of artifactual data in mobile recordings Mikhail Lebedev, and to allow analyses of brain activity in real working environments new portable sensors and Duke University, USA improved analyses approaches have to be developed. Hence, deployment of portable neuroimaging *Correspondence: technologies to real time settings could help assess cognitive and motivational states of personnel Klaus Gramann assigned to perform critical tasks. [email protected] THE “TRENDS IN NEUROERGONOMICS” RESEARCH TOPIC: A Received: 07 February 2017 BRIEF INTRODUCTION Accepted: 21 March 2017 Published: 05 April 2017 The eBook of this Frontiers Research Topic is divided into four sections, defined by the primary Citation: research methods used to address a variety of neuroergonomic research questions. The scientific Gramann K, Fairclough SH, topics range from air traffic control and automation, over mental load detection and the use of Zander TO and Ayaz H (2017) Editorial: Trends in Neuroergonomics. brain activity to control a system (brain computer interfaces, BCI), to physical work, rehabilitation, Front. Hum. Neurosci. 11:165. and training. Across the diverse research areas, the majority of studies in this Research Topic doi: 10.3389/fnhum.2017.00165 used electroencephalography (EEG), followed by functional near infrared spectroscopy (fNIRS), Frontiers in Human Neuroscience | www.frontiersin.org 1 April 2017 | Volume 11 | Article 165 Gramann et al. Editorial: Trends in Neuroergonomics reflecting the constantly growing use of these methods in wider variety of control commands in motor imagery-based neuroergonomics. At the same time this eBook clearly BCIs might lead to an accelerate brain-computer communication demonstrates a trend to investigate physical and cognitive activity while Callan et al. increase response speed in flight simulation by outside standard laboratory settings, moving neuroergonomics using a passive BCI based on MEG. The former study provides “into the wild.” In addition, traditional methods like the insights into the use of control commands to increase BCI- measurement of eye movements, pupil metrics, (ECG), and based system communication while the latter study demonstrates established imaging approaches like functional magnetic the potential to decode motor intention faster than manual resonance imaging (fMRI) are used in combination with other control in response to hazardous change in the system interaction methods to better understand the physiological responses to cycle. Roy et al. investigate mental workload based on auditory cognitive or physical tasks and their coupling to hemodynamic evoked potentials. The authors present a new minimal intrusive changes. The different sections include original research articles, paradigm that paves the way to monitor operators’ mental state but also reviews and opinion pieces. Here, we provide short in real-life settings to allow adaption of the user interface without summaries as an orientation for the interested reader. interfering with the primary task. Caywood et al. increase the The first section in this eBook thus comprises studies that interpretability of BCI models by using the approach of Gaussian used EEG to investigate ergonomic research questions with three Process Regression for assessing cognitive workload. Ewing et al. studies using EEG in a mobile setting. The first of these by describe the development of an adaptive game system that Jungnickel and Gramann uses a mobile brain/body imaging measures spontaneous EEG activity in real-time in order to adjust approach (MoBI; Makeig et al., 2009; Gramann et al., 2012, the difficulty level of the game. In two studies the concept of a 2014) to investigate the brain and behavioral dynamics of human biocybernetic control loop (Fairclough, 2009) is introduced in participants interacting with dynamically moving objects. The detail with a particular emphasis on validating EEG measures results indicate increased activity in parietal regions when active experimentally prior to their incorporation into an adaptive game physical behavior as compared to standard laboratory button system. press behavior was required to respond to relevant changes in Studies using EEG in combination with other methods show the environment. The findings point to changes in brain dynamic that different physiological parameters can lead to an improved states dependent on the behavioral state. The study by Wascher understanding of the construct under investigation. Ko et al. et al. demonstrates that mobile EEG allows for a non-obtrusive demonstrate the advantage of integrating the high resolution in assessment of mental fatigue in natural working situations. The the time and spatial domain for EEG and fMRI, respectively, in a authors investigate EEG variations time-locked to eye-blinksasa stop-signal paradigm. Their results from multimodal recordings new tool to unobtrusively monitor cognitive processing in real- provide new insights into the complex brain networks underlying life environments. Mijovic´ et al. also use EEG in a naturalistic inhibitory control in naturalistic environments. Using EEG in work environment to show that instructed responses can increase combination with ECG and fNIRS, Ahn et al. investigate mental attention as reflected in brain dynamics without changes in fatigue in drivers. They show that a combination of different response parameters. The results point to the possibility to use physiological measures substantially improves the classification instructed responses to increase attentional processing without of sleep deprived or well-rested drivers. Scheer et al. investigate compromising work performance in manual assembly tasks. the demands on mental resources during a closed-loop steering Again, explicitly allowing movement of participants, Meinel task in simulated car driving scenarios. The results indicate an et al. demonstrate that EEG can be used to improve motor impact of steering demands on event-related EEG activity for rehabilitation approaches. Better performance in movement tasks task-irrelevant distractor probes allowing for an evaluation of can be achieved by identifying comodulation of different sources mental workload in steering environments. in the EEG before a movement is executed. The results provide The second section summarizes the use of fNIRS in traditional participant-specific prediction of performance fluctuations that stationary settings but also in new mobile applications. The could be used to enhance neuroergonomic and rehabilitation first study of these, Von Lühmann et al. describe the scenarios. The last study by Zander et al. investigates how well development of a wireless and low-cost open source fNIRS a passive brain-computer Interface can work in an autonomous hardware with details on system concept, hardware, software driving scenario using a dry EEG system. The results reveal and mechanical implementation. The proposed system was tested comfort issues but acceptable usability of the tested EEG system
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